The Role of Lebanon in the COVID-19 Butterfly Effect: The B.1.398 Example.

In the present study, we provide a retrospective genomic surveillance of the SARS-CoV-2 pandemic in Lebanon; we newly sequence the viral genomes of 200 nasopharyngeal samples collected between July 2020 and February 2021 from patients in different regions of Lebanon and from travelers crossing the Lebanese-Syrian border, and we also analyze the Lebanese genomic dataset available at GISAID. Our results show that SARS-CoV-2 infections in Lebanon during this period were shaped by the turnovers of four dominant SARS-CoV-2 lineages, with B.1.398 being the first to thoroughly dominate. Lebanon acted as a dispersal center of B.1.398 to other countries, with intercontinental transmissions being more common than within-continent. Within the country, the district of Tripoli, which was the source of 43% of the total B.1.398 sequences in our study, was identified as being an important source of dispersal in the country. In conclusion, our findings exemplify the butterfly effect, by which a lineage that emerges in a small area can be spread around the world, and highlight the potential role of developing countries in the emergence of new variants.

Characterization of SARS-CoV-2 ORF6 deletion variants detected in a nosocomial cluster during routine genomic surveillance, Lyon, France.

During routine molecular surveillance of SARS-CoV-2 performed at the National Reference Center of Respiratory Viruses (Lyon, France) (n = 229 sequences collected February-April 2020), two frameshifting deletions were detected in the open reading frame 6, at the same position (27267). While a 26-nucleotide deletion variant (D26) was only found in one nasopharyngeal sample in March 2020, the 34-nucleotide deletion (D34) was found within a single geriatric hospital unit in 5/9 patients and one health care worker in April 2020. Phylogeny analysis strongly suggested a nosocomial transmission of D34, with potential fecal transmission, as also identified in a stool sample. No difference in disease severity was observed between patients hospitalized in the geriatric unit infected with WT or D34. In vitro D26 and D34 characterization revealed comparable replication kinetics with the wild-type (WT), but differential host immune responses. While interferon-stimulated genes were similarly upregulated after infection with WT and ORF6 variants, the latter specifically induced overexpression of 9 genes coding for inflammatory cytokines in the NF-kB pathway, including CCL2/MCP1, PTX3, and TNFα, for which high plasma levels have been associated with severe COVID-19. Our findings emphasize the need to monitor the occurrence of ORF6 deletions and assess their impact on the host immune response.

Evaluation of NGS-based approaches for SARS-CoV-2 whole genome characterisation.

Since the beginning of the COVID-19 outbreak, SARS-CoV-2 whole-genome sequencing (WGS) has been performed at unprecedented rate worldwide with the use of very diverse Next-Generation Sequencing (NGS) methods. Herein, we compare the performance of four NGS-based approaches for SARS-CoV-2 WGS. Twenty-four clinical respiratory samples with a large scale of Ct values (from 10.7 to 33.9) were sequenced with four methods. Three used Illumina sequencing: an in-house metagenomic NGS (mNGS) protocol and two newly commercialised kits including a hybridisation capture method developed by Illumina (DNA Prep with Enrichment kit and Respiratory Virus Oligo Panel, RVOP), and an amplicon sequencing method developed by Paragon Genomics (CleanPlex SARS-CoV-2 kit). We also evaluated the widely used amplicon sequencing protocol developed by ARTIC Network and combined with Oxford Nanopore Technologies (ONT) sequencing. All four methods yielded near-complete genomes (>99%) for high viral loads samples (n = 8), with mNGS and RVOP producing the most complete genomes. For mid viral loads (Ct 20-25), amplicon-based enrichment methods led to genome coverage >99 per cent for all samples while 1/8 sample sequenced with RVOP and 2/8 samples sequenced with mNGS had a genome coverage below 99 per cent. For low viral loads (Ct ≥25), amplicon-based enrichment methods were the most sensitive techniques. All methods were highly concordant in terms of identity in complete consensus sequence. Just one mismatch in three samples was observed in CleanPlex vs the other methods, due to the dedicated bioinformatics pipeline setting a high threshold to call SNP compared to reference sequence. Importantly, all methods correctly identified a newly observed 34nt-deletion in ORF6 but required specific bioinformatic validation for RVOP. Finally, as a major warning for targeted techniques, a loss of coverage in any given region of the genome should alert to a potential rearrangement or a SNP in primer-annealing or probe-hybridizing regions and would require further validation using unbiased metagenomic sequencing.

Whole Genome Sequencing of A(H3N2) Influenza Viruses Reveals Variants Associated with Severity during the 2016⁻2017 Season.

Influenza viruses cause a remarkable disease burden and significant morbidity and mortality worldwide, and these impacts vary between seasons. To understand the mechanisms associated with these differences, a comprehensive approach is needed to characterize the impact of influenza genomic traits on the burden of disease. During 2016⁻2017, a year with severe A(H3N2), we sequenced 176 A(H3N2) influenza genomes using next generation sequencing (NGS) for routine surveillance of circulating influenza viruses collected via the French national influenza community-based surveillance network or from patients hospitalized in the intensive care units of the University Hospitals of Lyon, France. Taking into account confounding factors, sequencing and clinical data were used to identify genomic variants and quasispecies associated with influenza severity or vaccine failure. Several amino acid substitutions significantly associated with clinical traits were found, including NA V263I and NS1 K196E which were associated with severity and co-occurred only in viruses from the 3c.2a1 clade. Additionally, we observed that intra-host diversity as a whole and on a specific set of gene segments increased with severity. These results support the use of whole genome sequencing as a tool for the identification of genetic traits associated with severe influenza in the context of influenza surveillance.